MindKind: A mixed-methods protocol for the feasibility of global digital mental health studies in young people version 1; peer review: 1 approved ...
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Wellcome Open Research 2021, 6:275 Last updated: 21 DEC 2021
STUDY PROTOCOL
MindKind: A mixed-methods protocol for the feasibility of
global digital mental health studies in young people [version
1; peer review: 1 approved with reservations]
The MindKind Consortium
v1 First published: 15 Oct 2021, 6:275 Open Peer Review
https://doi.org/10.12688/wellcomeopenres.17167.1
Latest published: 15 Oct 2021, 6:275
https://doi.org/10.12688/wellcomeopenres.17167.1 Reviewer Status
Invited Reviewers
Abstract
Background: While an estimated 14-20% of young adults experience 1
mental health conditions worldwide, the best strategies for
prevention and management are not fully understood. The ubiquity of version 1
smartphone use among young people makes them excellent 15 Oct 2021 report
candidates for collecting data about lived experiences and their
relationships to mental health. However, not much is known about the
1. Rahul Shidhaye , Pravara Institute of
factors affecting young peoples’ willingness to share information
about their mental health. Medical Sciences, Loni, India
Any reports and responses or comments on the
Objective: We aim to understand the data governance and
engagement strategies influencing young peoples’ (aged 16-24) article can be found at the end of the article.
participation in app-based studies of mental health. We hypothesize
that the willingness to participate in research is impacted by their
ability to be involved in how their data is collected, shared, and used.
Methods: Here, we describe the MindKind Study, which employs
mixed methods to understand the feasibility of global, smartphone-
based studies of youth mental health. A pilot 12-week app-based
substudy will query participants’ willingness to engage with remote
mental health studies. Participants will be randomized into one of four
different data governance models designed to understand their
preferences, as well as the acceptability of models that allow them
more or less control over how their data are accessed and used.
Enrolees will receive one of two different engagement strategies. A
companion qualitative study will employ a deliberative democracy
approach to examine the preferences, concerns and expectations of
young people, with respect to remote mental health research. We also
detail our engagement with young people as co-researchers in this
study. This pilot study is being conducted in India, South Africa and
the United Kingdom.
Conclusions: This study is expected to generate new insights into the
feasibility of, and best practices for, remote smartphone-based
studies of mental health in youth and represents an important step
Page 1 of 16
Wellcome Open Research 2021, 6:275 Last updated: 21 DEC 2021
toward understanding which approaches could help people better
manage their mental health.
Keywords
mental health, anxiety, depression, young people, mobile health
study, qualitative research, data governance, engagement
Corresponding author: The MindKind Consortium (solly.sieberts@sagebase.org)
Competing interests: Soumitra Pathare receives grant funding from Grand Challenges Canada, Wellcome Trust, India Alliance, National
Institute of Mental Health (USA), Thakur Family Foundation, Mariwala Health Initiative, Comic Relief (UK), Indian Council of Medical
Research (ICMR) for various projects and has had paid consultancies for Botnar Foundation, Commonwealth Nurses & Midwives
Foundation, World Health Organization in the past 5 years. Tamsin Ford receives funding from Place2Be, a third sector organisation that
provides mental health training and counselling within schools to contribute to their research and outcome monitoring.
Grant information: This project was commissioned by the Mental Health Priority Area at Wellcome Trust.
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Copyright: © 2021 The MindKind Consortium. This is an open access article distributed under the terms of the Creative Commons
Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly
cited.
How to cite this article: The MindKind Consortium. MindKind: A mixed-methods protocol for the feasibility of global digital mental
health studies in young people [version 1; peer review: 1 approved with reservations] Wellcome Open Research 2021, 6:275
https://doi.org/10.12688/wellcomeopenres.17167.1
First published: 15 Oct 2021, 6:275 https://doi.org/10.12688/wellcomeopenres.17167.1
Page 2 of 16Wellcome Open Research 2021, 6:275 Last updated: 21 DEC 2021
Introduction quickly13, so understanding the factors that would attract and
Anxiety and depression have a major impact on the lives of maintain participation are important for the success of such
millions of individuals, particularly for adolescents and young research.
people. For adolescents globally, mental health conditions
constitute a major burden of disease, with one out of seven To this aim, we describe the MindKind study, a mixed-methods
adolescents estimated to have mental health problems in 20191. approach to understand the governance, technical and scientific
According to the World Health Organization, up to 20% of feasibility of developing a global mental health database of
children and adolescents worldwide experience one or more digital data collected from young adults using smartphones.
mental health disorders with three-quarters of mental health Our two-pronged approach pairs a pilot smartphone-based study
related illnesses developing by their mid-20s2. This burden has with a qualitative study to understand the behaviour, concerns,
been exacerbated by the physical and mental impacts of the and desires of young people with respect to mobile mental
current Sars-Cov-2 pandemic3. Despite the high prevalence health research. We hypothesize that young peoples’ willingness to
rate, strategies for prevention and approaches to treating mental participate in research is impacted by their ability to be involved
health in young people remain limited due to a myriad of in how their data is collected, shared, and used. To that end,
factors, such as variable life circumstances and lived we will directly test a range of data governance models
experience, lack of resources, shortage of trained health care that promote participant-led open data practices14. The
providers, and social stigma associated with mental disorders. overarching goals of the project are to: (a) prototype and test
mechanisms to successfully empower young people to be involved
To understand what kind of approaches will work for whom in data management; (b) enable rapid and convenient data
and why in relation to prevention, treatment and managing the collection; (c) identify the governance model that young people
ongoing difficulties of anxiety and depression in young people, support to share their data with mental health scientists; and
it is important to gather data about the lived experience of (d) understand the factors affecting young peoples’ willingness
young people with anxiety or depression. In order to study the to engage with and contribute to such a databank. This
variable impact of “lived experience” on disease trajectories international effort is being piloted in three countries; India,
and management, longitudinal data on lived experience must be South Africa and the United Kingdom (UK), which were
collected across large study cohorts to detail the many aspects chosen to have a range of economic, socio-cultural and regu-
of that individual’s life, that may relate to or impact their mental latory landscapes. Throughout the project we centre our work
health state, such as sleep, physical activity, social relationships, on the voices of young people. We engage young adults with an
etc. Such data can be collected directly from individuals using interest in mental health as co-researchers and partners
digital technologies like smartphones. The ubiquity of smart- throughout the entire process, from design, prototyping, and
phones and other modern technologies provides an opportunity for testing of the study frameworks.
remote data collection of mental health in a convenient and
non-intrusive manner. For longitudinal data especially, it can Methods
ensure rapid data collection with ease, in real life settings, Ethics
without any travel or administrative barriers4. Additionally, it MindKind has been approved by the relevant Institutional
opens avenues for large-scale data collection across borders Review Boards and Ethics Boards in the U.S. (WIRB #20212067),
that can yield data rich in the variability that could be key in UK (University of Cambridge - Department of Psychol-
understanding mental health. ogy Research Ethics Committee: Ref. PRE.2021.031 and
University of Oxford: Ref. R73366/RE00), South Africa
The use of smartphones to capture participant-reported (Walter Sisulu University #029/2021 and the Department of
outcomes or e-diaries has become commonplace in health and Higher Education and Training), India (India Law Society
mental health research5,6. In addition, mobile apps and digital #ILS/242/2021), and as of September 2021 is also currently
sensors have been used in a number of research studies to under review by the Health Ministry Screening Committee (HMSC)
monitor symptom variability7–11. Along with administering in India.
surveys, smartphone-based applications also enable the collec-
tion of data using evidence-based scales and instruments on fac- Study overview
tors that impact youth mental health along with passive data, MindKind is a feasibility study being conducted in India,
such as the number of steps taken or screen time12. Moreover, South Africa, and the UK to capture the preferences and
engaging youth through smartphones can have added benefits perspectives of youth from a set of diverse cultural backgrounds.
as they can be an effective medium to better understand young The mental health data collected are not intended for analysis,
people’s social, physical and emotional lives. However, the but rather to understand the degree to which young adults are
collection, processing, and use of such data, which is considered willing to share this information. The study’s aims are
highly personal by many individuals, will need to be sensitive underpinned by the assumption that youth involvement in
to the interests of the young people contributing their data. Very such a databank is essential to its success15. In addition to the
little is known about the factors influencing young peoples’ study design, we describe the roles of Youth Advisors and our
willingness to participate in such research, and across many Data Use Advisory Group in the development process. The study
domains, participation in remote studies tends to drop off will employ mixed methods and consists of two substudies.
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A quantitative substudy will query participants’ data govern- significant change in day-to-day functioning and contribution to
ance preferences or acceptability, to understand how study community19.
participants would like their data governed and accessed.
It will also collect demographic information and mental Young people are involved in this study in two ways: first
health indicators, in order to understand the willingness of as co-researchers20, including study design, data collection,
participants to share information about their mental health curation and analysis, and dissemination, and secondly as study
on an ongoing basis. Participants will interact with a custom participants (in the quantitative and qualitative substudies),
Android app to enable rapid and convenient data collection. whose preferences will inform the structure of the eventual
Through a purpose-build app, we will examine such factors mental health databank. By including young people as
as consent to enrol, the types of data contributed, and duration co-researchers and data contribution partners, we aim to:
of data contribution. Various engagement strategies will also be 1) centre our work from a social justice and health equity lens;
tested to determine how short- and long-term engagement may 2) improve the quality and appropriateness of our study design,
be impacted e.g., offering participants the choice of selecting data collection, and data analysis; 3) empower young people
which of the potential indicators of mental health--‘active as active agents for change in their communities; and 4) build
ingredients’- they contribute to the databank. Here we define capacity among young people around mental health and
‘active ingredients’ as factors which have been shown to mental health research20,21.
influence mental health such as sleep, body movement/exercise,
social connections, and positive activities16. Youth co-researchers have several formal roles within the
project team:
The qualitative substudy will collect data from deliberative
democracy sessions; a method that joins communities in Professional youth advisors: a professional youth advisor
discussions of complex ethical issues by providing educa- (PYA) was hired in each of the three countries to serve as
tion to inform discussion and engaging participants in dialogue a core member of the research team. PYAs were selected by
leading to iterative consensus building17, regarding youth data- the local site team based on their age (18–24 years old), lived
bank governance preferences. It aims to (1) identify the consensus experience with mental health challenges, and prior experience
data governance model(s) for an open yet privacy-preserving working on mental health-related, adolescent-focused, or
global mental health databank, from the perspective of community engagement projects and programs. As core
multinational young people; and (2) understand the concerns, members of the research team, PYAs contribute to help guide
hopes, and expectations of multinational youth for such a decisions and research directions. In addition to providing
databank with regards to the return of value to youth participants their own voice in research decisions, PYAs liaise between the
and youth participation in databank governance. country-specific Youth Panel Advisory Groups (YPAGs; see
below) and the project teams, facilitating YPAG meetings,
Interplay between quantitative and qualitative studies synthesizing panel feedback, providing recommendations to
Both studies aim to understand the best way to develop other project teams, and presenting their findings at monthly
a global mental health databank for young people. The qualita- Steering Committee meetings. Each PYA led the recruitment
tive study generates data that can be implemented in future itera- for their respective YPAG and is responsible for conducting
tions of the app-based (quantitative) study. In its pilot phase, the regular check-ins with YPAG members to ensure engagement
quantitative study asks questions about engagement and throughout the project.
acceptability within certain constraints, whereas the qualita-
tive study asks about an ideal databank in an ideal scenario. Youth panel advisory groups: single-country YPAGs have
The qualitative study exposes participants to options for data 12–15 members per site, ages 16–24 (UK) or 18–24 (India,
management and storage that are not feasible to ask of partici- South Africa), with lived experience of mental health chal-
pants in the quantitative study. Additionally, whereas the quan- lenges. YPAG members were purposefully recruited to ensure
titative study collects data that researchers can compare across balance by gender, geographic regions, and educational
regions, the qualitative study puts participants from different background when possible. YPAGs meet twice per month via a
countries in direct dialogue with one another in the second video conferencing platform to discuss key aspects of the study
round of deliberative sessions. This multinational session data design and data collection. Meetings are recorded and PYAs
will offer insights into why certain preferential differences may capture feedback in a study database after each meeting. YPAG
arise in the app-mediated study. members also participate in asynchronous virtual chats (e.g.,
via WhatsApp) which are particularly important for engag-
Youth engagement ing YPAG members with limited data and/or internet access.
Structure. This study leverages community-based participa- YPAGs participate in small group projects and feedback
tory research approaches18, which seek to involve community rounds in between meetings as needed.
stakeholders and researchers as equal partners, to guide the
engagement of young people with lived experience of mental International youth panel: the international youth panel (IYP)
health challenges. We define “lived experience” as self- has 14 members, with three to five representatives drawn from
reported experience with mental health challenges that cause a each of the YPAGs. The IPY meets virtually on a monthly basis
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and is a place for the youth across countries to get to know one Quantitative substudy
another and to come to consensus around key decisions. IYP Study design: governance models
members were selected democratically by each YPAG. IYP The quantitative substudy is designed to assess the prefer-
meetings are recorded and feedback is captured within a study ence and acceptability of different data governance models and
database. engagement patterns over time. Given the sensitivity of men-
tal health data, we are seeking to understand whether prospec-
Global youth panel: the global youth panel (GYP) has 15 youth tive participants of a future global mental health databank have
representatives, ages 18–30, from each of the three country a preference for data governance models which give partici-
sites, as well as other high- and middle-income countries pants more control over who can access the data and for what
(e.g., United States, Canada, Kenya, Nigeria). Members purpose. We will also seek to understand whether these prefer-
were selected by the academic study team based on their past ences impact enrolment. In order to assess these questions, youth
experience on youth panels and in advocacy groups for men- participants will be randomized, in equal proportions, to one
tal health issues among young people. The GYP meets virtually of four different governance experiences (Figure 1), the first of
on a bi-monthly basis to provide high-level feedback on project which (Group A) assesses preference, with the remaining three
decisions that could inform future testing and rollout of the (Groups B, C, D) addressing acceptability of various data
MindKind study beyond our current three study locations. GYP governance models.
meetings are recorded and feedback is captured within a study
database.
In order to assess the preference of young people with
regards to data governance, participants randomized to Group
Feedback loops. Feedback from youth panels informs and
A will be prompted to select how researchers are allowed to
guides project decision making as much as possible. Regardless
access their data, and who controls access to the data. The selec-
of their ability to be implemented as part of this initial, feasibil-
tion of these options was informed by the disparate preferences
ity study, all youth recommendations and decisions are docu-
expressed by youth co-researchers versus the DUG.
mented and will be revisited for future, larger-scale studies based
on this work.
Choice 1: How should researchers be allowed to access the study
Additionally, PYAs provide regular feedback on their roles data?
in the project to the academic study team, allowing for 1. Researchers should be allowed to download a copy.
meaningful review and revision of youth role descriptions and
deliverables, identifying opportunities to improve equitable 2. Researchers should only be allowed to access the data in a
collaboration and devise study-specific metrics of successful secure server.
youth engagement and study co-production.
3. Researchers should only be allowed to see a recreated
The data usability group data set, not the real data. If researchers want to study
To advise on the scientific and analytical value of the future the real data set, they have to ask the data steward to run
youth global mental health databank, we recruited and their analysis for them. The steward only gives the
regularly convene a Data Usability Group (DUG) to provide researcher back the result, not the data.
their perspectives on scientific uses for a global mental health
databank, governance models, data storage and accessibility, Choice 2: Who controls the data?
data use agreements, and researcher qualifications. The DUG has
1. Democracy: study participants who select this option
20 researchers from seven countries (Australia, Brazil,
get to vote on how the data is used, and the most popu-
India, Nigeria, South Africa, United Kingdom, and United States).
lar terms are applied to all data regardless of how an
DUG members are drawn from the fields of open science and
individual votes. The results of the vote are shared with
data sharing, study teams associated with Wellcome ‘active
participants before data are shared. Any participant who
ingredients’ commission16, and adolescent mental health
disagrees with the vote may withdraw from the study.
researchers and clinicians. The DUG meets virtually every three
See Appendix 122 (Extended data) for voting questions.
to six months, with more frequent asynchronous communication
(e.g., follow up emails and surveys). Recommendations and 2. olunteer community review panel: participants selecting
V
feedback from the group is presented at Steering Committee this option may choose to volunteer to serve as a data
meetings and consolidated into a database for tracking. use request reviewer, taking one-week turns in this role
on a rotating basis. Researchers will submit a statement
MindKind study design telling the reviewers why they want to use the data.
To participate in the MindKind study, youth participants must The reviewers will apply a set of criteria to decide yes
live in one of the participating countries and be legally able to or no. These criteria will be determined in advance by
provide consent (age 16–24 in the UK or 18–24 for India and the whole group of volunteer reviewers.
South Africa). Youth are eligible if they can follow study
instructions, read and understand English, and have access to an 3. Professional review panel: a paid panel will review data
Android mobile phone (for quantitative substudy participation requests. This panel is a group of participants paid by
only). the funder of the databank and may include research
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Figure 1. Governance study design. Potential quantitative substudy participants are randomly assigned to one of four consent
models. Group A is designed to assess what practices are preferable to study participants. Groups B-D are designed to assess the
acceptability of current standards to models that allow participants a greater voice and more data security.
professionals (e.g., research ethics professionals). from the databank following strict data security rules.
As above, researchers will have to submit a statement Data may be used, unrestricted, by both commercial and
telling the reviewers why they want to use the data. non-commercial researchers.
The reviewers would decide yes or no, based on a set
of criteria to which will be developed in advance by the • Youth informed democracy with download (Group C):
group. Study participants will vote as described in the
Democracy Choice above. Under this model, researchers
Participants randomized to Group A will be asked to select are allowed to download a copy of the data.
their data governance choices prior to consenting. Addition-
• Youth informed democracy without download (Group D):
ally, participants who select ‘Democracy’ for choice two will be
Study participants will vote as described in the
asked to provide their preference on four questions about data
Democracy Choice above. Under this data governance
terms of use (Appendix 122, Extended data), which constitutes
model, data may only be accessed via a restricted server.
their democratic vote (Figure 1).
In order to assess the acceptability of current governance In quantifying the difference in enrolment rates between
standards relative to those that give participants a greater voice participants in each group, we can assess whether democratic
regarding how data are accessed and used, participants that are determination of access terms improves enrolment (Group C vs
randomized to Groups B, C, or D will be presented with a Group D), and whether restricting data download additionally
pre-specified governance model. These three ‘acceptability’ improves enrolment (Group D vs Group C).
experiences were selected by the research team to test (1) whether
democratic determination of data terms improves enrolment Study design: engagement
over current researcher-driven norms, and (2) whether limit- Following enrolment in the study, participants will use the
ing data access to a restricted server further improves enrolment. study app to complete daily activities and surveys for the
Specifically, the three models are: course of the 12-week study (Figure 2). The study consists of
• Research norm (Group B): This option presents cur- questions about four domains (‘active ingredients’ (AIs)) which
rent researcher community norms for data use, whereby have been shown to influence mental health: sleep, body move-
researchers will be able to download a copy of the data ment/exercise, social connections, and positive activities16.
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Figure 2. MindKind app study design. The 12-week study is composed of three, four-week rotations focusing on different topics
influencing mental health (sleep, body movement, social connections and positive experiences). Participants will be randomized into
one of two arms: the first of which allows participants to select their topics of focus and the second of which assigns the topics to
which participants are exposed.
Participants will focus on one of these domains in four-week Recruitment
rotations. For example, a participant may receive questions The quantitative substudy aims to recruit 4500 young people
about body movement for weeks one to four, positive activities (1500 from each country) to download the study app, with a
for weeks five to eight, and social connections for weeks nine minimum of 10% of the 4500 young people recruited having
to 12. See the “Surveys and data collection” section for more details lived experience of anxiety and depression. The sample size was
on the content of these domain surveys. selected based on expected engagement13 in order to achieve a
program goal of 100 participants per country completing the
In order to understand whether the choice of survey domain 12-week study.
impacts a participant’s short- or long-term engagement in the
study, we will independently randomize participants into two Rolling recruitment will begin in the third quarter of 2021.
different arms (in equal proportion). Participants in the first arm Youth will be recruited in the following ways:
select their AI topic at the beginning of weeks one, five, and 1. hrough social media given limitations on in-person
T
nine. Participants in the second arm are randomly assigned to activities during the ongoing COVID-19 pandemic. Posts
their AIs for each of the three, four-week rotations (Figure 2). and advertisements will be placed on popular youth
Page 7 of 16Wellcome Open Research 2021, 6:275 Last updated: 21 DEC 2021
accessible social media platforms such as Instagram, use habits (Appendix 323, Extended data). ‘Your health’
Twitter, Facebook, LinkedIn, Reddit, and WhatsApp to includes questions pertaining to physical ability (WHODAS 2.0
reach young people in each of the three study countries. (12-item)26), depression (PHQ-927), anxiety (GAD-728), and
history and management of mental health (Appendix 323,
2. o ensure that data collection is representative of a
T
Extended data). These baseline questionnaires are administered
broad population in each country, the three sites will
on study day zero (Figure 3). On the following day, participants
collaborate with intersectoral organisations (organisa-
begin their first AI-rotation for weeks one to four. The second
tions working on sexual and reproductive health research,
and third rotations occur weeks five to eight and nine to 12,
disabilities, sexuality, race/caste etc) with the help of
respectively (Figure 2).
emailers and posts.
3. ach of the sites will also reach out to partner (youth)
E Surveys and active data collection: The questions posed to
organisations and spread the word within their networks participants throughout the study focus on the interplay
along with using existing researcher contacts. between mood and four different AIs (sleep, social connections,
body movement or physical activity, and positive activities)
4. We will also recruit students at educational institutions (Figure 2–Figure 3). Study participants focus on one AI at a
(e.g., schools, colleges and universities) with the help time, in four-week rotations. On days one to six of the week,
of posters/flyers, and existing contacts between the site participants are asked a standard mood question:
team and identified institutions.
5. etworks of young people will be tapped into by PYA
N Pick the response that describes how you felt today:
and YPAG participants for snowball recruitment. ◦ Worst ever
Recruitment materials such as social media posts, posters,
◦ Bad mood
flyers, videos etc, will be developed in English for all the ◦ Average
three sites. Additionally, to reach a more diverse population, ◦ Good mood
recruitment materials will be translated to other languages in
South Africa (IsiXhosa and seSotho) and in India (Hindi,
◦ Best ever
Marathi and Tamil). However, the study app will be available
along with a short (three to five item) AI-specific
only in English.
questionnaire (Appendix 229, Extended data). They are also
prompted to journal on an AI-specific or general topic on one
Youth co-researchers have been heavily involved in the of those days. On the seventh day, participants are asked to
development of recruitment plans, providing feedback on the complete a long survey related to their AI topic (Insomnia
recruitment materials and helping disseminate the final materi- Severity Index (seven-item)30, UCLA Loneliness Scale
als to ensure that all recruitment materials are youth friendly (three-item)31, International Physical Activity Questionnaire
and culturally appropriate. (seven-item)32,33, Behavioural Activation for Depression Scale34
for the sleep, social connections, body movement and positive
Due to concerns about cellular data costs in South Africa, study activities AIs, respectively), as well as PHQ-927 and GAD-728 to
participants in this country will be given a small stipend to get a deeper understanding of their mood (Figure 3).
subsidize their data plans in order to facilitate participation.
Stipends of R150 will be paid per four weeks of participation Passive data collection: Participants can opt in to provide
in the quantitative substudy. Similarly, a small stipend pool exists passive data collection about their phone activity and environ-
for participants in India who find it difficult to pay for data. ment in order to understand their phone use habits. The sta-
However, given the relatively low expense for cellular data here, tistics collected are daily screen time (a daily log of when
the need is not expected to be widespread. No stipends are the phone’s screen is unlocked), charging time (a log of
offered for participants of the quantitative substudy in the UK. when the phone is connected to its charger), battery statis-
tics (a log of battery charge throughout the day via the Android
Data collection ACTION_BATTERY_CHANGED call), data usage (hourly
On enrolment, a baseline survey is administered to catalogue reporting of amount of data transmitted and received), ambient
the participant’s background and experiences with mental light as measured by the phone’s light sensor (sampled for
health. For ease of administration, these are divided into four ten seconds every five minutes in order to minimize battery
sections. ‘About you’ includes the topics demographics and consumption). No information will be collected that could vio-
socio-economic status (Appendix 323, Extended data). ‘Your late a participant’s privacy, such as information about specific
environment’ includes food security (USDA Food insecurity activities or apps used on the phone, call logs, or the content
survey (six-item))24, neighbourhood safety and cohesion of messages. No identifiable location data will be collected.
questions (PhenX Neighbourhood Safety, and PhenX Collective
Efficacy)25 and questions related to history of exposure to Technical implementation: The study will be implemented in
violence (Appendix 323, Extended data). ‘Your habits’ includes two separate pieces of technology. Eligibility checking, account
questions pertaining to hobbies, physical activity and phone creation and enrolment occurs via a website which has been
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Figure 3. Baseline, daily, and weekly surveys. MindKind is a 12-week study consisting of a baseline survey followed by four-week
rotations focusing on a single “active ingredient” (AI). On the seventh day of the week, a long survey is administered consisting of a standard
instrument pertaining to the topic of the AI, as well as PHQ-9 and GAD-7. During the remaining days participants receive short questionnaires
including a standard mood question and three to five AI-specific questions. Participants are prompted to journal on one of those days. At
the beginning of weeks five and nine, a new AI is presented (Arm 2) or selected by the participant (Arm 1).
optimized for mobile device experiences. Once a participant Data management: Data from both the enrolment website and
has enrolled, they are prompted to download the MindKind study app will be sent to the Sage Bridge Server as json files.
Study App from the Google Play store. The app requires an Coded study data, consisting of survey responses and passive
Android phone running Android 5.0 or higher. Participants use data measurements, will be exported to Sage’s data sharing
their phone number as a mechanism to create an account on the service, Synapse, for access by the study team35. Synapse is a
enrolment website, and to login to their account on the study general-purpose data and analysis sharing service where mem-
app. Each time they request to login, a unique code sent to bers can work collaboratively, analyse data, share insights
their phone via SMS validates their login. and have attributions and provenance of those insights to
share with others. Synapse is developed and operated by Sage
Both applications will store data in the Bridge Server, a set of Bionetworks as a service to the health research community.
web services developed and operated by Sage Bionetworks. Programmatic access to Synapse via R and Python Clients
Bridge exposes a REST style web services API designed to allow allows us to curate the json files from the surveys into tabular
collection and management of mobile health data from a variety formats by survey type in order to allow for analysis.
of apps. This service has been used by Sage and other research
organizations to support a variety of health studies on both Data analysis plan
the Android and iOS platforms. Bridge provides apps the All analyses described below will be performed within-site as
ability to securely create accounts for participants, and record well as across-site, adjusting for site. A sensitivity analysis
consent and other personal information separately from will be performed, excluding South Africa, due to the potential
study data intended to be shared with research teams. confounding introduced by participant payment.
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Governance preference: This analysis leverages the Group A for how long. Using a logistic regression model, we will assess
(Figure 1) selections for Option 1 and Option 2 to understand the potential differences in data sharing aggregate statistics.
the degree to which study participants have a preference about Time to dropout can be analysed using a proportional hazards
how their data are accessed, both on who determines which model with censoring at the study end. For each of these three
investigators can access the data, and by what means they access analyses, we will also secondarily examine the effect of the
the data. Outcome variables for this aspect of the substudy governance model on engagement.
are the prospective participant’s (1) model choice for govern-
ing standard for the data and (2) model choice for researcher Qualitative substudy
access to the data. The primary analysis will be a summarization Study design
of participant preference for each of the two questions. We will employ a deliberative democracy approach for this
A chi-square test will be used to assess the statistical signifi- study17. Deliberative democracy is a method for community
cance of the differences observed between the three options. engagement in the complex ethical issues surrounding emerg-
A secondary set of analyses will assess the degree to which age, ing technologies for which most people have not yet formed
gender, and self-reported present or past mental health issues strong opinions. Deliberative democracy is a distinct qualitative
are associated with governance model preference, both globally research approach, differing from focus groups by the pur-
and within-site. This analysis will also be performed with a poseful provision of educational intervention to enrich group
multinomial logistic regression adjusting for these three variables. discussion. Further, there is an emphasis on discussion lead-
ing to iterative revision of opinions as participants integrate new
Governance acceptability: This analysis leverages the enrol- information and others’ perspectives.
ment rate for Groups B-D to understand the degree to which a
We will conduct two rounds of deliberative democracy sessions.
governance model that improves usability and access by
In the first round, up to ten cohorts of five to seven partici-
investigators, affects study enrolment over models that give
pants will be convened per country (approximately 150 total
participants more control (i.e. democratic determination of data
participants). A sample size of n=50 per site is characteristic
terms) and offer better data security (i.e. secure server access
of deliberative democracy studies36. The individual group size
only). The outcome variable for this aspect of the substudy is
of five to seven participants is characteristic of a typical small
whether or not the prospective participant enrolled (yes/no).
group in in-person studies36,37. Each will explore data
A logistic regression to test the effect of the governance model
governance models and voice their concerns and hopes
will be fit, adjusting for age, gender, self-reported present
regarding data governance for a global mental health databank
or past mental health issues, and site (global model only).
for youth, identifying points of consensus and disagreement.
The primary comparisons of interest are Group C vs Group B
Standard educational materials will be co-created and
(democracy vs current norms) and Group D vs Group C (server
disseminated prior to the deliberative sessions to prepare
access vs data download). A secondary analysis will test an
participants. These materials may be disseminated as written
interaction term between the model and self-reported mental
or in other multi-media formats (e.g., audio, video). Participants
health issues.
will have the opportunity to ask the research team any
questions prior to the sessions. Cohorts will meet virtually
Engagement: The goal of this portion of the study is to for up to two hours.
understand participant engagement and compliance with the
study protocol during the course of the 12-week study. We In the second round of deliberation, we will convene up to
will measure participant engagement based on the following ten multinational cohorts; all participants in the multinational
metrics: 1) study completion rates, i.e. proportion of partici- sessions will be drawn from the first round. Again, cohorts
pants that remain active in the study through 12 weeks as well will meet for up to two hours in two 60-minute sessions.
as interim time points (e.g. four and eight weeks); 2) types of Each cohort includes six to eight participants: two to three
data (surveys and passive data streams) shared by participants participants from each country (60 total participants).
and for how long; 3) total active tasks completed; 4) time
to dropout (i.e. time point of the last task completed). This arrangement of sessions allows participants to: 1) develop
expertise over time both with content and with the deliberative
For study completion and interim participation, the binary approach; 2) appreciate the similarities and differences between
outcome variables ‘participation at time X’ (yes/no) can be country-specific and multinational perspectives on data
modelled using logistic regression to test the effect of the governance; 3) reflect on the intersection of these topics with
engagement model, adjusting for various socio-demographic their own lived experience.
factors (e.g. age, gender, self-reported history of mental health
challenges), governance model (self-choice, or specific model The quality of deliberative democracy sessions will be
presented) and site (global model only). For total task comple- evaluated using criteria proposed by DeVries et al., 201037,
tion, the number of tasks completed by a participant will be including equal participation of all participants, respect
modelled using Poisson Regression using the same independent for the opinions of others, willingness to adopt a social (rather
variables as previously stated. For assessing the types of data than individualistic) perspective, and reasoned justification for
shared by participants, we will compute the aggregate statistics one’s positions. These data will be gathered by the research
on the number of unique data types shared by participants and team participant exit surveys.
Page 10 of 16Wellcome Open Research 2021, 6:275 Last updated: 21 DEC 2021
Co-creation Discussion session data will be transcribed verbatim,
YPAGs and the IYP engaged in co-design with the academic de-identified, and checked for quality against audio recordings
study team on the following topics: a) ensuring representation by the academic research team. De-identified transcripts will be
from marginalized and vulnerable groups in recruitment and uploaded to a cloud-based qualitative data analysis platform
participation; b) developing study materials including: (NVivo). The academic research team, in collaboration with
informed consent, educational materials, and facilitator guides; youth researchers, will code each transcript on this shared
c) identifying the challenges of virtual discussions and platform. The study team will identify a priori codes based
developing mitigation strategies to address equal engage- on study goals, and emergent codes will be developed
ment and power imbalances; d) planning for involving youth iteratively during the coding process. Coding discrepancies
co-researchers in data analysis; e) dissemination of and access will be resolved through whole group discussion. Youth
to study findings in a way that is engaging and inclusive of the co-researchers will collaborate with the academic research
people who have participated. team in the analysis process. All analytical outputs will be
reviewed and ratified by the youth co-researchers and academic
Recruitment research team collectively.
Participants will be recruited directly through YPAG members
and existing volunteer rosters, existing researcher contacts, and
Discussion
snowball recruitment through these contacts. Further, social
The goal of this feasibility study is to further our
media (passive, active), direct email advertising, and posters
understanding of the potential issues and challenges with
may be used. Additionally, a single-time pop-up message in
developing a databank from remote, smartphone-based
the MindKind app will recruit from young people participating
assessments of mental health in youth. Our findings will then
in the quantitative substudy with a goal that half have previ-
inform the development of a larger global mental health
ous exposure to the study. Young people with lived experience
databank and any future evaluations. Both the quantitative and
of anxiety and/or depression will be preferentially enrolled.
qualitative study in the UK and South Africa are due to begin
imminently, with the Indian site to follow once governmental
Deliberative sessions will be stratified by age and co-enrolment approval is received.
or lack of co-enrolment in the quantitative substudy. Youth will
participate in sessions with others of similar age. For single
country sessions, there will be up to three age cohorts (e.g., We believe that the nature and extent of youth involvement
16- to 17-year-olds in the UK; 18- to 20-year-olds in all in shaping an ambitious global mental health databank is
countries; 21–24-year-olds in all countries). For multinational uncommon in current research practices. The involvement
sessions, there will be at least two age cohorts (e.g., 16- to of professional youth advisors in each of the sites, who
20-year- olds; 21- to 24-year-olds). In single country sessions, in turn establish and run young people advisory groups
we will aim for an equal distribution of participants across (YPAGs) has been critical in ensuring that the study design,
these two variables (i.e., age and co-enrolment in the methods, engagement strategies, and app design are tailored
quantitative substudy), but will have no fewer than one-third to young people. While the development of the professional
in each category, except for the UK age groups, which will youth advisor role requires capacity building that must be
have no fewer than one quarter of the total UK study population undertaken for them to meaningfully engage with the study,
enrolled in any one age category. Additionally, we will seek the benefits of involving young people directly are manifold.
a sample from a diversity of backgrounds in relation to gen- To the best of our knowledge, this is the first time multi-site pro-
der, geographic location, socioeconomic status, educational fessional youth advisors have been engaged quite so closely in
attainment, ethnicity, religion, and first language. We will shaping the course of a project aimed at improving adolescent
continue sampling participants until we have recruited a diverse mental health globally.
set of individuals.
Challenges
Data collection and analysis This study benefits from site teams working in different
There are two primary outputs of deliberative democracy contexts and is unusual in that two of the three study sites are
processes: deliberative output and analytical output38. Deliberative from low-to-middle income countries (LMICs). However, these
outputs are statements of consensus or disagreement that differences present some challenges. The sites have had to con-
arise directly from discussants. These statements will be textualize the data safety management and storage policies as per
captured by the facilitator and will be ratified by discussants the sites and country-level laws and policies. In a digital feasi-
themselves before the end of their cohort session. We will bility study, the sites have had to ensure that concerns regarding
employ the framework method39 to capture analytical outputs data transfer to the main study site, privacy, and implications on
regarding concerns, hopes, and expectations of discussants the use of data collected were fully considered as a consortium
on return of value for participation in such a databank and the along with the youth leads. Consistent, on-going consortium
concerns, hopes, and expectations of discussants regarding level meetings, consultations from experts on ethics, law and
youth participation. The framework approach is particularly mental health researchers were some of the processes taken
useful in multi-disciplinary research teams that include lay to ensure that the consortium is responsive to the ethical
people with less qualitative data analysis experience. and cultural requirements.
Page 11 of 16Wellcome Open Research 2021, 6:275 Last updated: 21 DEC 2021
This project has also faced planning and design challenges sessions in the UK, India, or South Africa may not be
imposed by the COVID-19 pandemic. Many efforts initially representative of young people as a whole in these coun-
envisioned as in-person, principally the youth panels, were tries or elsewhere. For example, due to the restrictions on the
transitioned to virtual venues. This has led to concerns about quantitative substudy, the study participants will include young
representation from marginalised and vulnerable groups, adults that have access to the internet on an Android device
impacted by the inability to own a device to access the internet, and are able to interact with the digital platform in English.
gendered use of technology, and language barriers since the The sites made accommodations for providing access to
meetings were primarily held in English. data/internet for youth to engage with the study application,
especially in low-middle income country settings. The qualita-
Integrating voices of young people also required strategies tive substudy allows for flexibility on the language, on access
for protection against harm. This resulted in each site creating to a device, and on the interaction with the study applica-
a safeguarding protocol that was contextually relevant for the tion, thereby allowing for a more diverse group of youth to
group. Safeguarding included taking all reasonable steps to opine on the study questions. This potential difference in
prevent any form of harm, abuse or neglect from occurring; representativeness is, however, expected and understanding
protecting people’s health, wellbeing and human rights; and these potential differences is part of this study. Moreover, the
further, taking reasonable steps to respond appropriately triangulation of data sources (app, group sessions, youth
when harm or abuse does occur. As part of the process, the study advisors’ feedback) will enable the consideration of similarities
was co-designed with young people and the consent forms and and differences between various sub-groups of young people.
study material explained the purpose of the study in a simple The study was not designed to assess mental health outcomes,
manner. and therefore any analyses of the data pertaining to these
outcomes must be interpreted with caution.
We anticipate future challenges in implementing this study.
For example, differences in ethical and institution specific Data availability
procedural requirements that could potentially lead to delayed Underlying data
start dates for some study sites, which has implications on No underlying data are associated with this article.
meeting the project timelines and milestones. Moreover, the
varied timeline across sites has implications on equal participation Extended data
from the study partners and youth engagement, such as Synapse: MindKind Databank
formation of the youth panels or recruitment of the study
• A
ppendix 1: (Democratic choice voting options, PDF
team members across sites.
format)22
We also anticipate that recruiting 1500 young people for the https://doi.org/10.7303/syn26067677.1
quantitative study in the three sites may be challenging
• Appendix 2: (Daily AI questions, PDF format)29
due to the size of this group proposed to be recruited and
specific constraints in contexts. For example, there are lower https://doi.org/10.7303/syn26067678.1
numbers of young Android phone users in the UK. In contrast,
the cost of accessing mobile data in South Africa may be • A
ppendix 3: (Eligibility and Baseline questionnaires,
prohibitive for many young people. We have made allowances PDF format)23
for this by subsidizing cellular data costs; however, this https://doi.org/10.7303/syn26067679.1
introduces an incentive for participation13 in the study and
introduces potential confounding in the enrolment and Data are available under the terms of the Creative Commons
engagement analyses. 1.0 “Universal” (CC0 1.0 public domain dedication)
With respect to the qualitative substudy, we anticipate that
conducting deliberative democracy sessions on data governance Acknowledgements
models with young people who may not necessarily be famil- We acknowledge and thank the members of our Youth Group
iar with the scientific literature may be another challenge. Advisory Panels in India, South Africa and the UK, the
To mitigate this, we have prepared detailed recruitment International Youth Panel, the Global Youth Panel, and the
strategies for each context and co-designed the educational Data Usability Group for their contributions to this project. We
material for deliberative democracy sessions along with youth acknowledge Dr Ramneek Ahluwalia and Anuysha Naidu for
advisors and YPAGs in each of the sites. Mock qualitative facilitating this research within Higher Health (South Africa).
sessions were also held with YPAGs by the youth advisors
to ensure the sessions planned were useful, accessible, and The MindKind Consortium
enjoyable for participants. Faith Oluwasemilore Adeyemi1,2, Patricia A. Areán3, Emily
Bampton4, Ljubomir Bradic5, Anne-Marie Burn1, Emma Carey1,
Limitations Sonia P. Carlson5, Pamela Y. Collins3,6, Tessa Concepcion6,
The primary potential limitation is that the views of those who use Meera Damji7, Megan Doerr5, Julia C. Dunbar5, Mina Fazel4,8,
the MindKind app and participate in the deliberative democracy Blossom Fernandes4, Gillian Finchilescu9, Tamsin Jane Ford1,10,
Page 12 of 16Wellcome Open Research 2021, 6:275 Last updated: 21 DEC 2021
Melvyn Freeman11,12, Isabell R. Griffith Fillipo3,13, Jay Hodgson5, 8
The Oxford Psychological Medicine Centre, Oxford University
Jasmine Kalha7, Minal Karani7, Michael R. Kellen5, Christopher Hospitals NHS Foundation Trust, Oxford, United Kingdom
G. Kemp14, Simthembile Lindani15, Lara M. Mangravite5, 9
Department of Psychology, University of the Witwatersrand,
Carly Marten5, Felicia Mata-Greve3, Emily Moore5, Erin Mounts5,
Johannesburg, Gauteng, South Africa
Lakshmi Neelakantan4, Larsson Omberg5, Lisa Pasquale5,
Soumitra Pathare7, Swetha Ranganathan7, Nichole Sams3, 10
Cambridge and Peterborough NHS Foundation Trust,
Erin Scanlan5, Himani Shah7, Sotirios Short11, Refiloe Sibisi11, Cambridge, UK
Solveig K. Sieberts5,*, Stockard Simon5, Sushmita Sumant7, 11
Higher Health, Higher Education and Training: Health, Wellness,
Christine Suver5, Chandre Van Vught11, Jennifer Velloza6,
and Development Centre, Pretoria, Gauteng, South Africa
Zukiswa Zingela16
12
Department of Psychology, University of Stellenbosch,
1
Department of Psychiatry, University of Cambridge, Cambridge, Stellenbosch, Western Cape, South Africa
United Kingdom
CREATIV Lab, University of Washington, Seattle, Washington,
13
2
Department of Psychology, University of Bath, United Kingdom United States
3
Department of Psychiatry & Behavioral Sciences, University of Department of International Health, Johns Hopkins University,
14
Washington, Seattle, Washington, United States Baltimore, Maryland, United States
4
Department of Psychiatry, University of Oxford, Oxford, United 15
Department of Psychiatry and Behavioural Science, Walter
Kingdom Sisulu University, Mthatha, Eastern Cape, South Africa
5
Sage Bionetworks, Seattle, Washington, United States, 16
Office of The Executive Dean, Faculty of Health Sciences,
6
Department of Global Health, University of Washington, Seattle, Nelson Mandela University, Gqeberha, Eastern Cape, South
Washington, United States Africa.
7
Centre for Mental Health Law and Policy, Indian Law Society, * Corresponding author: Solveig Sieberts (solly.sieberts@
Pune, Maharashtra, India sagebase.org)
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